Fitness Function for Energy Efficient Multipath Routing Protocol in MANETs T.RADHAKRISHNA V.
V.RAMAPRASAD II.M.Tech student, Department of ComputerScience, Professor, Departmentof Computer science,Sree Vidyanikethan Engineering CollegeTirupati, India. Sree VidyanikethanEngineering CollegeTirupati,India Abstract: MobileAd hoc network (MANET) is group of self-routing enabled devices that transmitamong themselves without any certain network infrastructure. Routing in MANETShas routes between nodes in a topology with many unidirectional links usingminimum resources.
Since routing protocols have role in MANETS, their energy-awareness makegreater network lifetime by efficiently using of the available energy. In allexisting single path routing schemes a new path-discovery process is meant oncea path failure is detected and it causes wastage of node measure. A multipath routing scheme is the alternativeto maximize the network lifetime. Energy, distances are the fitness values usedin the previous work to find the optimal path in multipath routing. In thiswork, it is proposed to use the network resource bandwidth as a fitness value.The calculations for selecting routes towards the destination will be accordingto energy, distance and also bandwidth. The proposed work is expected toimprove the performance of mobile ad hoc networks by prolonging the lifetime ofthe network. The performance will be evaluated in terms of throughput, packetdelivery ratio, end-to-end delay, routing overhead ratio, energy consumptionand then compare with the results of existing AOMDV protocol Keywords: Mobile Ad hoc network, routing protocol,multipath routing, fitness value 1.
INTRODUCTION:In recent daysthere is change in the computer performance, technologies in mobile communications.Mobile systems want ad hoc networks in which mobile nodes will align throughline. In MANETs, network safety is must by which the battery life of the nodesis feeble. To maintain the network period the routing protocol is sufficient toraise the intensity of the node. Multiple routing protocols base paths to rushthe packets i.e.
, route appeal is controllable by the point of supply to achievereality in concerning ways. MANETs will be classified into three generations:first, second and third generations. In 1970’s the ad hoc network firstgeneration are called Packet Radio Network (PRNET). In early 1980’s SurvivableAdaptive Radio Network (SURAN) evolved from PRNET. The function pack of MANETsproduced the routing code regulated and fix agents like PDA’S, palmtops,notebooks. Few codes like Bluetooth, IEEE 802.11(WLAN’S) are arranged tomaintain the MANETs.
For several years from 1970’s to 1990’s there are changesin the generations of MANET i.e., finally some standards are made to maintainthe MANET.
At any time the channel breaks, the Route Error is transmitted. Whenthis occurs the source transmit the package over the path to the destinationwithout any interruption. This can be done with the multipath routing protocol whichare referred to the one path routing protocol. In one path routing once thelink splits thepackets will not transmit.Whereas inmultipath routing, paths can be referred to send the data packets.
Fitness function is derived from ParticleSwarm Optimization (PSO) algorithm. Fitness Function is mostly used to find theideal route. The optimal path is the one with:· Lessdistance and· Exhaustless energy. The optimal path minimizes theenergy loss and increases the network period. Thus the proposed FF-AOMDVperformance in maximizing the network lifetime is possible in comparison withthe AOMDV. 1.1 Existing system:The researchproposed highlights the problem of energy consumption in MANET by engaging theFitness Function technique to optimize the energy consumption in Ad Hoc onDemand Multipath Distance Vector (AOMDV) routing protocol. The proposedprotocol is called Ad Hoc on Demand Multipath Distance Vector with the FitnessFunction.
(FF-AOMDV).The fitness function is used to discover the ideal pathfrom the source to the destination to decrease the energy consumption inmultipath routing 1.2 AOMDV Routing protocol:An on-demandrouting protocol, AOMDV has its roots in the Ad hoc On-Demand Distance Vector(AODV), a popular single-path routing protocol. AOMDV offers two key services:route discovery and route maintenance.
Compared with AODV, AOMDV’s additionaloverhead is extra RERRs and RREPs intended for multipath maintenance and discovery, along with extrafields to route control packets . Route discovery and route maintenance involvefinding multiple routes from a source to a destination node. AOMDV utilizesthree control packets: the route request (RREQ); the route reply (RREP); andthe route error (RERR).A new multipath routing protocol called the FF-AOMDVrouting protocol is proposed which is a combination of Fitness Function and theAOMDV’s protocol.
The route, which consumes less energy could possibly be (a)the route that has the shortest distance; (b) the route with the highest levelof energy, or (c) both. 2. LITERATURE SURVEY:Energy Efficiency:The authorsTejpreet Singh et al. 1 demonstrates that Energy efficiency and security arethe challenging tasks in the design of a routing protocol. Energy–efficientsecured routing protocol is proposed to get away from this challenge. Secureoptimized link state routing protocol is used to supply security to theprotocol. Node Identification to the network is declared and nodes are approvedby the access control. Access control entity signs a private key Ki, public keyKi and the certificate Ci needed to obtain the group key by an authorized node.
Group key distribution accepting the generated keys with messages supportreducing energy consumption. The group key distribution mechanism allowssubstitute of the group key periodically or when a node is removed. The cyclicdistribution suspends adversaries with the group key, but not a private key. Incommunity networks, an authorized user may send the group key to anon-authorized friend so as to the friend accesses network resources.
Anintrusion detection system (IDS) also triggers the group key distribution. Fig1. illustrates the group keydistribution mechanism Sudhakar Pandey et al 2 Networkaccomplishment can be enriched by using cross-layer approach. Application of sendingpower charge method to arrange communication power issues in decline of energyconsumption. ED is examined to consult the weight assisted with each node. D views for degreeand E views for energy. Energy consumption is reduced and network accomplishmentis enriched by Control overhead reduction while route discovery and dynamicimprovement of transmission power is done.
The energy model of wireless sensor networkcan be stated as the total energy consumption of the network, arrange all itsunits, be it sensor device components, energy used in routing or routemaintenance, topology maintenance or whosoever it may be. Creating an energymodel is an vital part of any protocol growth and its performance estimation.Here a network is treated with n mobile sensor nodes and single sink node thatis static. Energy consumed by sensor device: The sensor device consistsof processing units, sensing unit, memory unit and transceiver unit.
So, energyconsumption of each unit made considered as: E SensorDevice = E processor + E sensor + Ememory+Etransceiver (1) Where E Sensor Device is the energy consumed by a sensordevice, E processor is the energy depleted by the processing units, E sensor isthe energy use up by the sensing unit, E memory is the energy spent by thememory unit and E transceiver is the energy consumed by the transceiver unit. Sincenetwork lifespan is an vital aspect criterion Sensor nodes perform for years.clearly 70% of network’s energy is used in data communication. By getting average ofReceived Signal Strength (RSS) values, transmission power is improved byCross-Layer design approach for Power Control. S.Muthurajkumar et al 3 Two important aspects of Mobile Ad Hoc Networks (MANETs) areEnergy consumption and security. Using trust management, key management,?rewalls and intrusion detection security is provided in MANET. It is essentialto consider the energy and security aspects in routing algorithms since energyand security are important for communication.
Energy consumption can be reducedautomatically by the prevention of security attacks on routing protocols andcluster based routing. Trust score evaluation, routing andthreshold setting using the trust values are the phases in trust based securerouting algorithm. In trust score evaluation process the trust score forindividual nodes are calculated based on constraints like nodes which aregenuinely sending their acknowledgement to neighbors when they received thepackets are treated as first group and the nodes which drop more packets are considered as and the nodes which drop more packets areconsidered as group two nodes. Now, the initial trust score is computed usingthe Eq that represents the percentage of acknowledgements. TS1i=(ACK/RP)*100 (2) ACK = No. of acknowledgements sent to the neighbors , TS1i = First trustscore in percentage for ith node, RP = No. of packets received from neighbors second trust score is computed using Eq (3) which calculatesthe dropped packets TS1i=100-((DP/TDP)*100) (3) DP = No. of packets dropped, TDP = Total number ofpackets dropped in network.
TS2i = Second trust score percentagefor ith node. The overall trust score of the particular nodeis calculated using Eq. (4) TSi=(TSli+TS2i)/2 (4) TS1i = First trust score for node i, TS2i = -Secondtrust score for node I, TSi = Overall trust score for node i.
Fordeveloping a cluster based network a clustering scheme is developed withclusters. A Cluster based Energy Ef?cient Secure Routing Algorithm (CEESRA) is proposedfor providing effective routing. Malicious nodes can be avoided and detectedusing the trust score. A dynamic clustering technique not only uses lowmobility nodes, energy consumption, trust values and distance parameters forproviding the energy ef?cient secure routing algorithm. The proposed algorithmprovides better performance in terms of packet drop ratio, residual energy,security and throughput when compared to the existing techniques. N.Magadevi et al 4 The wireless nodes havelimited power resource in Wireless Sensor Networks.
To recharge the batteriesof the wireless nodes Wireless charging is an alternative. Using a singlemobile anchor a wireless recharging and also localization are proposed.Localization provides the position information. Static node is located by themobile anchor first and then it receives the battery level.
Later static nodesare recharged if the static node battery is lesser than the threshold limit. Fundamentalunit of sensor network is sensor node. It comprises of sensors, microprocessor, transceiver , memoryand power supply. An Adhoc network with a collection of number of sensor nodesis Wireless Sensor Network.
It is used in many ?elds like disaster rescue, intrusiondetection and in health care applications. Gateway between the WSN and theother network is sink node. Noise Ratio (SNR), increased ef?ciency, improvedrobustness and scalability are the advantages in WSN. In designing WSN thereare several challenges like software development, deployment, localization,hardware design, routing protocol and coverage. For effective datacommunication and computation sensor node must be accurate. In the advancementof wireless sensor networks effective localization system must be developed.
Rangefree localization algorithms do not require distance or angle measurements.Along with the wireless charging localization problem is addressed here. Sensorsenses the data and communicates with the base station through Multi hopcommunication. In Wireless Rechargeable Sensor Network an effective andcontrollable energy harvesting scheme is to be adopted. Thus proposed methodimproves the network’s lifetime.
Wen-KuangKuoet al 5 The energy consumption of battery-powered mobile devices can beincreased by measured in bits per Joule for MANETs. By jointly consideringrouting multimedia applications the energy ef?ciency (EE) is an essentialaspect of mobile ad hoc networks (MANETs). Based on the cross-layer designparadigm EE optimization is, traf?c scheduling, and power control a non convexmixed integer nonlinear programming is modeled as a problem. Branch and bound(BB) algorithm is devised to ef?ciently solve this optimal problem.
EEOPTIMIZATION PROBLEM:A MANET comprised of one set of stationary nodes N connected by a set L oflinks. We consider everylink l = nt-> nr to be directional,where nt and nr are thetransmitter and receiver of l,respectivelyMATHMATICAL MODEL FOR THEEE OPTIMIZATION PROBLEM:For every link l at every time slot t,binary variable as (), (5) Where ? = (1 ,…., T) and T is the total number of scheduled time slots.
Transmissionpower on link l at time slot t, i.e., , is continuously adjustedin given interval 0, pmax.constraint ( (6)Note thatbeing allowed to transmit does not necessarily mean a transmission actuallyoccurs, which is decided by the optimization algorithm. With recent advances ininformation and communication technology (ICT), MANETs become a promising andgrowing technique. Multimedia services like video on-demand, remote education,surveillance, and health monitoring are supported using MANETs. Energy is ascarce resource for mobile devices, which are typically driven by batteries.
Using cooperative multi-input-single-output transmissions authors maximized EEfor the MANET. By designing resource allocation mechanisms cross-layeroptimization can substantially enhance EE. By jointly computing routing path,transmission schedule, and power control to the network, link, and PHY layersacross-layer optimization framework is proposed to enhance EE. The transmission power of every active node ineach time slot is specified by the power control problem. To globally optimize ,anovel BB algorithm is developed. In terms of computational complexity proposedalgorithm outperformed the reference algorithm.
By exploiting the cross-layerdesign principle a solution to determine the optimal EE of the MANET isprovided. Distributed algorithms and protocols are designed to find the optimalEE. Any technique which can optimize non convex MINLP problem in a distributedmanner is not proposed. Thus distributed algorithms and protocols are developedusing approximation algorithms. The guarantee for acquiring the optimalsolution is the disadvantage of approximation algorithm.
A customized BBalgorithm for the optimization of the problem is proposed. A novel lower boundingstrategy and branching rule is designed and incorporated in the proposed BBalgorithm. To optimize EE of MANETs distributed protocols and algorithms areimplemented. To improve EE of MANETs novel distributed protocols and algorithmsare developed. 3. PROPOSED SYSTEM:A newmultipath routing protocol called the FF-AOMDV routing protocol, which is acombination of Fitness Function and the AOMDV’s protocol. When a RREQ isbroadcast and received, the source node will have three types of information inorder to find the shortest and optimized route path with minimized energyconsumption. This include:1.
Information about network’s each node’s energy level 2.The distance of every route 3.The energy consumed in the process of route discovery. The source node will then sends the data packets viathe route with highest Energy level, after which it will calculate its energyconsumption. The optimal route with less distance to destination will consumeless energy and it can be calculated as follows: Optimumroute1=?(n)rene(v(n))/?vVene(v) (7) In this equation, v represents the vertices (nodes) in the optimum route rand V represent all the vertices in thenetwork. It compares the energy level among all theroutes and chooses the route with the highest energy level.The calculation of the shortest route is as follows: Optimumroute2=?(n)rdist(e(n))/?eE (8) Where e representsthe edges (links) in the optimum route randE represent all the edges inthe network. Thepseudo-code for the fitness function is provided and Simulations are conductedto run the FF-AOMDV protocol.
In this simulation, an OTcl script has beenwritten to define the network parameters and topology, such as traffic source,number of nodes, queue size, node speed, routing protocols used and many otherparameters. Two files are produced when running the simulation: trace file forprocessing and a network animator (NAM) to visualize the simulation. NAM is agraphical simulation display tool. It shows the route selection of FF-AOMDVbased on specific parameters. The optimum route refers to the route that hasthe highest energy level and the less distance.
Priority is given to the energylevel, as seen on the route with the discontinuous arrow. In another scenario,if the route has the highest energy level, but does not have the shortestdistance, it can also be chosen but with less priority. In some otherscenarios, if the intermediate nodes located between the source and destinationwith lesser energy levels compared to other nodes in the network, the fitnessfunction will choose the route based on the shortest distance available. .
Energy,distances are the fitness values used in the previous work to find the optimalpath in multipath routing. Fig. 2 Optimumroute selection same proposedFF-AOMDV protocol is used along with the bandwidth as a fitness value. Now thecalculations for selecting routes towards the destination will be according toenergy, distance and also bandwidth. The same performance metrics used in theexperiments: 1. PacketDelivery Ratio.
2. Throughput.3. End-to-enddelay.4.
EnergyConsumption.5. NetworkLifetime.are used hereto evaluate the results. Thus the proposed work is expected to improve theperformance of mobile ad hoc networks by prolonging the lifetime of thenetwork. The performance will be evaluated in terms of throughput, packetdelivery ratio, end-to-end delay, energy consumption and then compare with theresults of existing AOMDV protocol.
Available Bandwidth: Bandwidth is also known as the data transferrate. It describes the data sent out by means of connection over a specifiedtime and the bandwidth is expressed in bps. Bandwidth is the bit-rate of theexisting or the consumed information capacity uttered normally in metricmultiples of bits per second. As the bandwidth is kept high the energyconsumption is also high. The data packets send increases and the energyconsumed at each node is also high. The transmission power consumption is highbecause the packets send are more.
When the bandwidth is taken as a parameteralong with the distance and energy, energy consumption varies as:1. when distanceincreases energy consumption also increases and when the route distance is lessenergy consumed will be low.2. whenbandwidth is high energy consumption isalso high and when it is less energy consumed will be low. Thusbandwidth is the parameter considered here and the simulation hasscenarios like node speed, packet size and simulation time.simulations are doneby keeping the scenariosas:varying the packetsize(64,128,256,512,1024) and keepboth the node speed and simulation time fixed.
Packet delivery ratio,Throughput, End-to-end delay, Routing overhead ratio are the performance metrics used to test thescenarios. In the proposed system as the bandwidth is the other parameter themathematical model is to be find based on the three parameters energy, distanceand bandwidth. 5. CONCLUSION:Energyef?ciency (EE) is an essential aspect of mobile ad hoc networks(MANETs).secured routing protocol is proposed which is energy efficient andsecurity is provided for both link and message without relying on the thirdparty. A secure communication among the participating nodes is offered by theenvironment of MANETS. Energy consumption plays an important role in networklifetime.
Since network mobility is an important factor and network’s energy isconsumed in data communication, Cross-Layer design approach is used to enhancethe transmission power for power control. Energy consumption can be reduced bythe prevention of security attacks on routing protocols. Here to find theoptimal path in multipath routing, distance and energy are the fitness valuesused. It is proposed to use the network resource bandwidth and calculations inselecting the routes towards the destination will be according to the distance,energy and also bandwidth .Thus the proposed work minimizes energy consumptionand maximizes network lifetime. REFERENCES:1.TejpreetSingh,JaswinderSingh,and SandeepSharma,”Energyef?cient secured routing protocol for MANETs,” in Wireless Networks, Springer,pp-1001-1009,May2017.2.
SudhakarPandeyandDeepikaAgarwal,”AnEDBasedEnhancedEnergy Ef?cient Cross Layer Model for Mobile Wireless Sensor Network,” in NationalAcademy Science Letters., Springer, pp 421-427,December 2017. 3.S.Muthurajkumar,S.Ganapathyand M.Vijayalakshmi, “An IntelligentSecured and Energy Ef?cient Routing Algorithm for MANETs,” in Wireless personalcommunications ,Springer,pp 1753-1769,September 2017.4.N.Magadevi,V.JawaharSenthilKumarandA.Suresh, “Maximizing the Network Life Time of Wireless Sensor Networks Using aMobile Charger,” in Wireless personal communications .,Springer ,pp 1-11,2017.5.Wen-KuangKuoand Shu-Hsien Chu, “Energy Efficiency Optimization for Mobile Hoc Networks,”IEEE Access, pp 928-940,March 2016